MINIMUM ZETA: Difference between revisions

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As always, the authoritative documentation is at http://www.mpimf-heidelberg.mpg.de/~kabsch/xds/html_doc/xds_parameters.html#MINIMUM_ZETA= !
As always, the authoritative documentation is at http://xds.mpimf-heidelberg.mpg.de/html_doc/xds_parameters.html#MINIMUM_ZETA= !


== What is MINIMUM_ZETA? ==
== What is MINIMUM_ZETA? ==


MINIMUM_ZETA is a parameter determining how close reflections may be to the 'blind region' of reciprocal space to still be integrated. On the detector, the blind region consists of two cones starting at the direct beam position, and extending along the spindle, to both directions.
MINIMUM_ZETA is a parameter determining how close reflections may be to the 'blind region' of reciprocal space to still be integrated. On the detector, the blind region consists of two cones starting at the direct beam position, and extending along the spindle, to both directions.
A high value (corresponding to a large blind region) is "safe" but produces lower completeness because more pixels of the detector are considered to be in the blind region. The default of 0.15 is on the safe side. I routinely use 0.1, and 0.05 turns out to still be good.


== How could I check if a low value of MINIMUM_ZETA is beneficial for my data reduction? ==
== How could I check if a low value of MINIMUM_ZETA is beneficial for my data reduction? ==


It does not hurt to use a low value of MINIMUM_ZETA (e.g. 0.05) in INTEGRATE, because in CORRECT you may still choose higher values (i.e. you don't then have to re-run INTEGRATE if you want to test a different value).
It does not hurt to use a low value of MINIMUM_ZETA (e.g. 0.03) in INTEGRATE, because in CORRECT you may still choose higher values (i.e. you don't then have to re-run INTEGRATE if you want to test a different value).


Then, run CORRECT with the low values and with higher values and compare the resulting completeness and R-factors.
Then, run CORRECT with the low values and with higher values and compare the resulting completeness and R-factors.
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For a finer evaluation, you might want to inspect with [[VIEW]] the file 'rf.pck' of [[XDSSTAT]] .
For a finer evaluation, you might want to inspect with [[VIEW]] the file 'rf.pck' of [[XDSSTAT]] .


== Examples ==
== An example ==
Using the default value of MINIMUM_ZETA= 0.15, one obtains in CORRECT.LP:
 
We collected data at the SLS, beamline X06SA, on a MarCCD 225 detector. Below, I show the final output of CORRECT.LP and a mapping of R-factors on the surface of the detector (file rf.pck produced by XDSSTAT).
 
Using the former default value of MINIMUM_ZETA= 0.15, one obtains in CORRECT.LP (this is from a 2010 version of XDS):


  SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
  SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
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[[Image:zeta-0.15.png]]
[[Image:zeta-0.15.png]]


However with MIMUM_ZETA=0.1 the R-factors and completenesses get a bit better:
With MIMUM_ZETA=0.1 the R-factors and completeness stays the same, but a closer look (not unexpectedly) reveals that the total number of observed reflections rises:
  SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
  SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
  RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
  RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
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     total    1725574  506106    524178      96.6%      18.6%    19.2%  1691046    5.43    22.0%    43.1%    2%  0.783  216270
     total    1725574  506106    524178      96.6%      18.6%    19.2%  1691046    5.43    22.0%    43.1%    2%  0.783  216270


and the cones along the spindle are narrower:
obviously the cones along the spindle are narrower:
[[Image:zeta-0.1.png]]
[[Image:zeta-0.1.png]]


Finally, with MINIMUM_ZETA=0.01 the statistics get even better:
Finally, with MINIMUM_ZETA=0.01 the number of observed reflections gets even higher:
  SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
  SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
  RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
  RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
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and there are few reflections missing in the blind region:
and there are few reflections missing in the blind region:
[[Image:zeta-0.01.png]]
[[Image:zeta-0.01.png]]
Finally, we may take a look at FRAME.pck and see that very few reflections are missing. The resolution of this image is not good enough to actually see the circles but one can see that all observed reflections are indeed hit by predictions.
[[Image:ms688-frame.png]]
From looking at rf.pck of many datasets, it is my experience that at the SLS (beamline X06SA), the R-factors along the spindle are better than perpendicular to it, which is quite surprising (and should be investigated). Therefore it is clear that in particular for these data it is a good thing to decrease MINIMUM_ZETA because accurately measured reflections are added to the data set.
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